# mcp
**Category:** 💻 Developer Tools
**Repository:** https://github.com/Coresignal-com/coresignal-mcp
**npm Downloads (last month):** 9111
**Views:** 0
**Installs:** 0
**Upvotes:** 0
**Directory Page:** https://allmcps.com/mcp/mcp-77
## Description
Fresh company, employee, and jobs records in real time.
## Claude Desktop Quick Installation
Heuristic fallback — verify the package name and runner against the repository README before running it. Uses `npx` (confidence: low):
```json
"mcpServers": {
"mcp": {
"command": "npx",
"args": ["-y","mcp-77"]
}
}
```
## Documentation & README
# Coresignal MCP v2
The official [Model Context Protocol](https://modelcontextprotocol.io) server for [Coresignal](https://coresignal.com) — bring fresh B2B data on **895M+ employees**, **70M+ companies**, and **468M+ job postings** straight into your AI assistant.
```bash
https://mcp.coresignal.com/mcp/v2
```
Search in plain natural language, pull full records, enrich contacts with verified emails, and export large result sets as downloadable files — all from Claude, Cursor, Codex, VS Code, or any other MCP-compatible client.
---
## Features
- **OAuth 2.1 authentication** — sign in with your Coresignal dashboard account; no API keys in config files.
- **Natural-language search** with match evidence in every result row, so you can see *why* each record matched.
- **Cost transparency** — every response reports `credits_consumed`, and expensive calls ask for confirmation before spending.
- **Field discovery** — `entity_fields` finds the right field names by keyword, free, without loading the full 300+ field vocabulary into context.
- **File downloads** — large result sets are stored server-side and returned as a download link instead of flooding the chat.
- **`artifact_read`** pages delivered files back into the conversation for free — works even in clients with no filesystem access.
## Prerequisites
- A [Coresignal account](https://dashboard.coresignal.com) with an active subscription (credits) and a team API key provisioned in the dashboard. The MCP server resolves your team's key automatically after sign-in — you never paste it into a config file. No subscription yet? Start with the **7-day free trial** — it includes **2,000 credits**. See the [plan comparison](https://coresignal.com/pricing/#plan-comparison).
On first connection your client opens a browser window to sign in to the Coresignal dashboard. That's the whole setup — no environment variables, no secrets.
---
## Client setup
Claude Desktop
Claude Desktop supports remote MCP servers natively via **Connectors**:
1. Open **Settings → Connectors → Add custom connector**.
2. Name: `Coresignal`, URL: `https://mcp.coresignal.com/mcp/v2`.
3. Click **Add**, then **Connect** — a browser window opens to sign in to your Coresignal dashboard account.
> **Important — enable file downloads:** Claude Desktop blocks downloads from domains it doesn't know. To download result files (large fetches are delivered as links), add `mcp.coresignal.com` to the **Domain allowlist** in Claude Desktop settings (on Team/Enterprise plans your admin manages this). Without it, download links from the server will be blocked — though you can always read the data back in-chat with the free `artifact_read` tool instead. See [File downloads](#file-downloads--the-domain-allowlist).
Claude Code
```bash
claude mcp add --transport http coresignal https://mcp.coresignal.com/mcp/v2
```
Then inside a session run `/mcp`, select **coresignal**, and complete the browser sign-in. Re-run `/mcp` any time you need to re-authenticate.
Codex (OpenAI Codex CLI)
```bash
codex mcp add coresignal --url https://mcp.coresignal.com/mcp/v2
```
A browser window opens to sign in to your Coresignal dashboard account.
Cursor
Add to `~/.cursor/mcp.json`:
```json
{
"mcpServers": {
"coresignal": {
"url": "https://mcp.coresignal.com/mcp/v2"
}
}
}
```
Cursor detects that the server requires authentication and shows a **Needs login** prompt — click it to complete the browser sign-in.
OpenCode
Add Coresignal MCP:
```bash
opencode mcp add coresignal --url https://mcp.coresignal.com/mcp/v2
```
Authenticate:
```bash
opencode mcp auth coresignal
```
A browser window opens to sign in to your Coresignal dashboard account.
Visual Studio Code
Run **MCP: Add Server** from the Command Palette, choose **HTTP**, and enter the URL — or add to `.vscode/mcp.json`:
```json
{
"servers": {
"coresignal": {
"type": "http",
"url": "https://mcp.coresignal.com/mcp/v2"
}
}
}
```
VS Code prompts you to authorize the server on first use and handles the OAuth flow in your browser.
Cline
Add to `~/.cline/data/settings/cline_mcp_settings.json`:
```json
{
"mcpServers": {
"coresignal": {
"type": "streamableHttp",
"url": "https://mcp.coresignal.com/mcp/v2",
"disabled": false
}
}
}
```
Open Cline MCP interface:
```bash
cline mcp
```
From menu select **Authorize OAuth** and select **coresignal**. Cline will handle the OAuth flow in your browser.
---
## File downloads & the domain allowlist
Large results (and any call with `delivery="url"`) are not dumped into the chat to save LLM input tokens. Instead the server stores the rows as a file and returns a **signed HTTPS download link** that expires after **1 hour**:
```json
{
"delivery": "url",
"url": "https://mcp.coresignal.com/mcp/v2/artifacts/…?exp=…&sig=…",
"artifact_name": "employee_fetch-baf941dd4f8c4dfe.jsonl",
"count": 500,
"credits_consumed": 10000
}
```
From here, the agent gets at the data in one of three ways:
1. **The agent downloads the file itself** — in clients with shell access, the agent will typically `curl` the link to disk and analyze the file locally with `grep`/`jq`/pandas.
2. **The agent reads it back in-chat** — in clients with no shell and no filesystem, the agent calls `artifact_read(artifact_name, offset, limit)` instead, paging through the file in slices over the MCP session. This is **free** and works everywhere, so nothing floods the chat.
3. **You download it manually** — if the agent itself isn't allowed to fetch the link (domain not allowlisted, sandbox without network access), click the link, save the file, and tell the agent where it is: *"I've downloaded the file to ~/Downloads/employee_fetch-….jsonl — analyze it from there."* Works in any client that can read local files.
> **Prefer the download when your client supports it.** `artifact_read` is free in Coresignal credits, but not in LLM tokens: every page it returns becomes part of the conversation and is re-billed as input tokens on each subsequent turn. Each page is also trimmed to a fixed token budget — a full employee record is ~8k tokens, so a single page carries only a handful of full records regardless of the `limit` you ask for. Reading a large file that way takes hundreds of calls and can exhaust the context window before you reach the end. A downloaded file costs essentially no tokens — the assistant can filter thousands of rows locally with `grep`/`jq` and surface only the answer. That's why it pays to get downloads working up front (domain allowlist, sandbox network access) and keep `artifact_read` for clients that can't download or for eyeballing a few rows.
**If downloads are blocked, nothing is lost:** the records are already stored and paid for — read them with `artifact_read`. Never re-run a fetch to "recover" a file; that bills every record a second time.
---
## Tools
| Tool | What it does | Cost |
| --- | --- | --- |
| `entity_search` | Natural-language search over employees, companies, or jobs | 20 credits per search (flat) |
| `entity_fields` | Keyword search over an entity's ~300 field names | Free |
| `entity_fetch` | Pull full (JSONL) or projected records, by search handle or by id | 20 credits per employee/company record, 1 per job record |
| `email_enrich` | Verified business emails for employee ids (CSV) | 10 credits per email **found** (misses are free) |
| `artifact_read` | Page rows back out of a delivered file | Free |
### `entity_search`
Searches `employee`, `company`, or `job` records with a plain-language query:
> *"Senior Python developers at fintech companies in French"*
Every call costs a flat **20 credits** and returns:
- `total_count` — the exact number of records the query matched,
- up to 20 preview rows (`limit=0` returns just the count), each showing the fields the query matched on — the *evidence* for why each result is there,
- a `cache_id` — a 1-hour handle to the search that **saves credits and time**: pass it to `entity_fetch` and the matched records are collected straight away — no need to re-run (and re-pay for) the search, and resolving the `cache_id` itself is free. Record ids stay server-side, so nothing bulky ever passes through the conversation.
### `entity_fields`
Free, instant lookup of field names by meaning — `"salary"` finds the compensation fields, `"current job title and seniority"` finds `active_experience_title`, `experience.position_title`, etc. Use it to build the `fields` list for a custom-scope fetch without ever loading the full field vocabulary into context.
### `entity_fetch`
Collects records — either up to 20 hand-picked ids from search results, or up to **1,000 records per call** via a `cache_id`. Billing is per record found: **20 credits** for employees/companies, **1** for jobs.
### `email_enrich`
Verified, deliverable business emails for up to 1,000 employee ids — **10 credits per email found**; not-found ids are free. EEA/UK contacts are not accessible (GDPR).
### `artifact_read`
Reads a delivered file back over the authenticated MCP session, a page at a time — **free**, since the records were billed when they were fetched. This is what makes file delivery work everywhere, including chat clients that can't open a link or touch a filesystem.
---
## Example prompts
### Market scan
> *"Find B2B SaaS companies in the Nordics with 50–200 employees that raised funding in the last two years."*
### Build a lead list with verified emails
> *"Search for heads of data at US companies with 500+ employees. Fetch 20 full profiles to a file with verified emails."*
### Deep-dive a single company**
> *"Pull the full record for flo.health — funding rounds, headcount growth, and current job openings."*
...
---
## Credits & billing
| Action | Credits |
|---|---|
| `entity_search` (any `limit`, including 0) | 20 per search |
| `entity_fetch` — employee or company | 20 per record found |
| `entity_fetch` — job | 1 per record found |
| `email_enrich` | 10 per email found; misses free |
| `entity_fields`, `artifact_read` | Free |
Every response includes `credits_consumed` — the actual billed amount, so a discrepancy (sent 1,000 ids, billed for 950 records) tells you exactly how many ids weren't found. The server never spends silently: fetches confirm field scope with you first, and a fetch that can't be delivered fails *before* any credits are spent.
Credits are drawn from your team's Coresignal subscription — manage keys and billing in the [dashboard](https://dashboard.coresignal.com). New to Coresignal? The **7-day free trial comes with 2,000 credits** — that's 100 searches, or 100 employee/company records, or a mix — see the [plan comparison](https://coresignal.com/pricing/#plan-comparison).
## Links
- [Coresignal](https://coresignal.com) — data coverage, plans, and pricing
- [Coresignal dashboard](https://dashboard.coresignal.com) — account, team, API keys, credits
- [API documentation](https://docs.coresignal.com/api) — the underlying data APIs
[](https://smithery.ai/servers/coresignal/coresignal)